One of the most important methods in high quality automobile and other vehicle or machine production involves the inspection of the exterior appearance (i.e. the quality of the paint finish on a part). Usually, an automobile shell, for example, receives at least four coatings including a protective coat, an adhesion aid coat, a paint coat and a clear coat. Defects occurring in the coating method of a properly prepared surface that may diminish the perceived quality of the exterior paint include, but are not limited to, dust, hair, metallic particles, over spray, incomplete spray, stripping and flake penetration. Inspection for such defects will ensure the exterior quality of the product from the customer's point of view.
Previously, evaluation of the quality of the paint finish was often based on human inspection, which can be a tedious and subjective method and one that requires meaningful skill and training. Other inspection procedures have been based on the use of charge-coupled device (CCD) optical sensors that sense imperfections through light reflected off of the finished surface. However, this technique is not particularly effective for complex, curved and/or hidden geometries (i.e. automobile bodies) because of its sensitivity and dependence on reflection and scattering angles.
In addition, it has been generally known to use infrared cameras to inspect certain products (i.e. semiconductor chips) for surface anomalies or defects. However, such inspection techniques are based solely on the spatial analysis of pixel values with that of known (standard) values without any account for the temporal behavior of the pixel values (e.g., change of temperature over time).
In addition, while other techniques have been utilized to measure the change of temperature over time, such techniques do not compare measured change of temperature of pixels of the same data file to that of surrounding pixels, and therefore fail to efficiently and effectively detect subsurface anomalies. Moreover, many inspection procedures require the need for a known non-defective area within a thermal profile for thermal deviation determinations, and others require continuous acquisition of a sequence of data files. Such procedures can also require operator intervention, significant time requirements, and/or computational complexities not suited for realtime applications.
As such, there is a desire for improved systems and methods capable of inspecting not only surface, but subsurface anomalies in multi-layered paint coatings, and in other related surfaces.